Author: David C, Bankless; Compiled by: Baishui, Golden Finance

As major companies rush to invest in software that can observe, reason and act on its own, artificial intelligence agents have recently become a major technology (and not just in the cryptocurrency space). These systems, sometimes called autonomous agents, promise to transform daily life—they might one day plan our schedules, shop online for us, or even build software without our direct help.

ChatGPT provided a critical spark that took advanced artificial intelligence from a futuristic idea to a widely used tool, proving that these models can learn and adapt in real time. AI agents are thrust into the spotlight as developers realize that AI can do more than just answer text prompts—such as handling tasks like managing calendars or coding.

Although still in its early stages, the potential of these systems continues to be recognized. That being said, AI agents can be difficult to master initially. In this article, we will clearly define them, how agents differ from regular “bots” or “workflows”, and then outline their synergy with blockchain. Let's get started.

AI agents are dynamic software systems designed to handle tasks with minimal human supervision. They use advanced AI tools to process data inputs (such as text, images, or blockchain records) to achieve specific goals. Unlike simple robots that follow strict rules for automation, AI agents bring intelligence, adaptability, and autonomy to their tasks.

Agents are often confused with bots, which are simply automated tools that perform functions based on predefined parameters. For example, a bot might follow a script to send an alert, place an order, or collect data when certain conditions are met, essentially operating through an "Action A triggers Action B" workflow. While robots are efficient at repetitive tasks, they strictly adhere to the rules set by their creators and lack the ability to adapt or learn.

Agents, on the other hand, leverage advanced techniques such as large language models (LLMs) to understand context, learn from interactions, and adapt to unforeseen circumstances.

This autonomy allows them to improve their methods in real time to better achieve their goals, even in changing environments. By combining automation with intelligence, agents can handle complex tasks that require situational awareness and intentionality, providing capabilities that go far beyond the limitations of traditional robots.

Over time, this flexibility can allow them to become personal assistants, financial managers or autonomous problem solvers in a range of applications.

While this cycle has been known as the AI ​​x Cryptocurrency cycle for some time, AI agents have become particularly popular in our industry recently.

While their initial use cases may seem simple, or something like GOAT or other "chatbots," the synergy between the two technologies turns out to be more fundamental. First, since many agents provide services, they also require payments that traditional financial infrastructure cannot provide them with. For example, opening a bank account or signing a contract often requires meeting with a banker or notary. Since AI agents are not actually human, they do not have passports or any necessary banking documents – making it difficult for them to interact with traditional finance and collect or make payments.

However, encryption solves this problem.

On a blockchain, it doesn’t matter whether participants are humans or software, meaning agents can own digital assets, make or receive payments for services, or interact directly with smart contracts, thereby solving the current financial system restrictions imposed on them. Furthermore, once these contracts are deployed, they can be used by anyone or anything, including AI agents. This arrangement contrasts with traditional finance, where each new entity must apply for and receive approval, whereas users on the blockchain (whether human or artificial intelligence) have access to all intelligence running on the blockchain contract.

Additionally, since many blockchains enable open source protocols, AI agents will likely have a wider range of tools to integrate with, giving them a broader toolbox to accomplish on-chain (or even off-chain) tasks, thereby increasing their autonomy and expanding their potential impact.

In addition to providing agents with the economic demand they need, blockchain also plays a key role in addressing concerns about "black box" artificial intelligence. With AGI becoming a matter of when, not if, many fear that AI in its current opaque state could create serious imbalances and lead to unintended consequences, posing a huge threat to society. However, by running on a decentralized network, the operation of artificial intelligence is transparent, difficult to monopolize, and can prevent abuse or single points of failure. Cryptozoology can therefore serve as a safeguard against this behavior, allowing the behavior of AI and AI agents to be verified on-chain.

In short, AI agents change the way we think about software and automation by introducing intelligence, adaptability, and independence—expanding the possibilities that are typically predefined by simple robots outside of workflow.

While agents can operate in dynamic environments, whether involved in planning, trading or interacting with real-world applications, by leveraging blockchain, these agents can overcome the limitations imposed on them by traditional finance, Significantly improve its potential to deliver services and achieve goals. Coupled with the transparency of decentralized networks, this convergence of AI and cryptocurrency promises to usher in an era where agents can confidently navigate financial services and keep their processes verifiable on-chain. As the capabilities of AI agents and blockchain ecosystems continue to evolve, their synergy will reshape how we process on-chain andThrough off-chain large-scale tasks, we create a future marked by higher intelligence and greater achievements.